{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_points = [\n",
    "    \"harry potter\",\n",
    "    \"dumbledore\",\n",
    "    \"snape\",\n",
    "    \"voldemort\",\n",
    "    \"the deathly hallows\",\n",
    "    \"the infinity stones\",\n",
    "    \"crypto\",\n",
    "    \"ut austin\",\n",
    "    \"llms\",\n",
    "    \"lions\",\n",
    "\n",
    "    \"new girl\",\n",
    "    \"the office\",\n",
    "    \"parks and recreation\",\n",
    "    \"austin, texas\",\n",
    "    \"luka doncic\",\n",
    "    \"solana\",\n",
    "    \"virtual memory\",\n",
    "    \"airbnb\",\n",
    "    \"portland\",\n",
    "    \"tabasco\"\n",
    "]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from benchmark import benchmark\n",
    "\n",
    "conciseness_sonar = []\n",
    "informativeness_sonar = []\n",
    "accuracy_sonar = []\n",
    "\n",
    "benchmark(\"sonar-small-online\", data_points, conciseness_sonar, informativeness_sonar, accuracy_sonar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "conciseness_mistral = []\n",
    "informativeness_mistral = []\n",
    "accuracy_mistral = []\n",
    "\n",
    "benchmark(\"mistral-7b-instruct\", data_points, conciseness_mistral, informativeness_mistral, accuracy_mistral)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "conciseness_mixtral = []\n",
    "informativeness_mixtral = []\n",
    "accuracy_mixtral = []\n",
    "\n",
    "benchmark(\"mixtral-8x7b-instruct\", data_points, conciseness_mixtral, informativeness_mixtral, accuracy_mixtral)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comparing Conciseness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "bar_width = 0.2\n",
    "x = np.arange(len(data_points))\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "bar1 = ax.bar(x - bar_width, conciseness_sonar, bar_width, label='sonar')\n",
    "bar2 = ax.bar(x, conciseness_mistral, bar_width, label='mistral')\n",
    "bar3 = ax.bar(x + bar_width, conciseness_mixtral, bar_width, label='mixtral')\n",
    "\n",
    "plt.xlabel('Subjects')\n",
    "plt.ylabel('Score (0 to 1000)')\n",
    "plt.title('Comparing Perplexity Models (Conciseness)')\n",
    "plt.xticks(x, data_points, fontsize=4)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sonar: avg: 730.0, std dev: 148.66068747318505\n",
      "mistral: avg: 720.0, std dev: 140.0\n",
      "mixtral: avg: 725.0, std dev: 129.9038105676658\n"
     ]
    }
   ],
   "source": [
    "print(\"sonar: avg: \" + str(np.average(conciseness_sonar)) + \", std dev: \" + str(np.std(conciseness_sonar)))\n",
    "print(\"mistral: avg: \" + str(np.average(conciseness_mistral)) + \", std dev: \" + str(np.std(conciseness_mistral)))\n",
    "print(\"mixtral: avg: \" + str(np.average(conciseness_mixtral)) + \", std dev: \" + str(np.std(conciseness_mixtral)))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comparing Informativeness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "bar1 = ax.bar(x - bar_width, informativeness_sonar, bar_width, label='sonar')\n",
    "bar2 = ax.bar(x, informativeness_mistral, bar_width, label='mistral')\n",
    "bar3 = ax.bar(x + bar_width, informativeness_mixtral, bar_width, label='mixtral')\n",
    "\n",
    "plt.xlabel('Subjects')\n",
    "plt.ylabel('Score (0 to 1000)')\n",
    "plt.title('Comparing Perplexity Models (Informativeness)')\n",
    "plt.xticks(x, data_points, fontsize=4)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sonar: avg: 890.0, std dev: 53.85164807134504\n",
      "mistral: avg: 885.0, std dev: 47.69696007084728\n",
      "mixtral: avg: 875.0, std dev: 43.30127018922193\n"
     ]
    }
   ],
   "source": [
    "print(\"sonar: avg: \" + str(np.average(informativeness_sonar)) + \", std dev: \" + str(np.std(informativeness_sonar)))\n",
    "print(\"mistral: avg: \" + str(np.average(informativeness_mistral)) + \", std dev: \" + str(np.std(informativeness_mistral)))\n",
    "print(\"mixtral: avg: \" + str(np.average(informativeness_mixtral)) + \", std dev: \" + str(np.std(informativeness_mixtral)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Comparing Accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "bar1 = ax.bar(x - bar_width, accuracy_sonar, bar_width, label='sonar')\n",
    "bar2 = ax.bar(x, accuracy_mistral, bar_width, label='mistral')\n",
    "bar3 = ax.bar(x + bar_width, accuracy_mixtral, bar_width, label='mixtral')\n",
    "\n",
    "plt.xlabel('Subjects')\n",
    "plt.ylabel('Score (0 to 1000)')\n",
    "plt.title('Comparing Perplexity Models (Accuracy)')\n",
    "plt.xticks(x, data_points, fontsize=4)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sonar: avg: 935.0, std dev: 35.70714214271425\n",
      "mistral: avg: 920.0, std dev: 33.166247903554\n",
      "mixtral: avg: 912.5, std dev: 21.650635094610966\n"
     ]
    }
   ],
   "source": [
    "print(\"sonar: avg: \" + str(np.average(accuracy_sonar)) + \", std dev: \" + str(np.std(accuracy_sonar)))\n",
    "print(\"mistral: avg: \" + str(np.average(accuracy_mistral)) + \", std dev: \" + str(np.std(accuracy_mistral)))\n",
    "print(\"mixtral: avg: \" + str(np.average(accuracy_mixtral)) + \", std dev: \" + str(np.std(accuracy_mixtral)))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
